Evaluation Methods for Aeration Parameters in Flotation Separation Modelling with Neural Network Applications

This study is dedicated to the application of neural network technologies for determining aeration parameters in order to predict the efficiency of flotation separation. Within the framework of the research, digital technology solutions were actively employed, including a neural network for segmentation at the stage of determining the granulometric characteristics of bubbles and a convolutional neural network module for determining the froth layer height. An analysis was conducted to examine the variation in the statistical parameter d32, which characterizes the bubble size distribution, as a function of flotation time and measurement height. The analysis revealed that the d32 values determined by neural network processing remained within the range of acceptable dispersion and are therefore suitable for subsequent analytical procedures. Furthermore, a comparative evaluation of the obtained size distributions indicated the absence of statistically significant differences between the neural network measurements and manually labelled data with a p-value equal to 0.64. A neural network for object detection was used to record the height of the froth layer during the experiment to obtain a time series, that were subsequently processed with data processing approaches including Savitzky–Golay and Singular Spectra Analysis. Based on the analysis of the sum of the obtained dependences, a criterion is proposed and modeled for evaluating the selectivity of frother by connecting the diameter of bubble in pulp and bubble in froth. Based on the modeling results, it was determined that the optimal range of bubble sizes and froth size ratios for MIBC is constrained to d32 values ranging from 1.058 to 1.089 mm, with the ratio of froth bubble radius to d32 ranging from 1.302 to 2.098, depending on the floatability ratios of the respective fractions. When employing OPF, the values for d32 fall within the interval of 0.868 to 1.113 mm, while the Dₓ parameter ranges from 0.559 to 0.931.